Kathryn J. Jervis, Gerson M. Goldberg andAlan C. Cutting
Excerpted from: Kathryn J. Jervis, Gerson M. Goldberg and Alan C. Cutting, Inner-city Hospital Closures: Financial Decision or Impediment to Access?, 38(3) Journal of Health Care Finance (Aspen) 22, 22-23, 35-36 (Spring, 2012) (83 Footnotes Omitted)
This study uses a financial ratio model and a behavioral model of health services use to examine whether poor hospital financial performance or other non-financial factors affected hospital closure in poor and largely minority urban communities. Prior research attempted to identify determinants of hospital closure that included financial and non-financial factors, such as hospital characteristics and environmental influences with mixed results. As in other studies, we too examine financial factors that affect hospital closure, as we would expect financially distressed hospitals to close. However, because patient access to health care may outweigh financial considerations, we identify factors to represent inner-city needs for access to health care based on a behavioral model of health services use. According to Williams, et al., “the hospitals that closed may have provided needed services. Thus concerns over ... diminished access to care may signal the need for some type of corrective policy actions concerning hospital closures.”
From our study, financial ratio variables indicate that high debt levels lead to hospital closure, though evidence from our other financial ratios is inconclusive. When [p23] considering factors from the behavioral health services use model, we find that urban hospitals with a high number of minorities are significantly more likely to close, similar to other hospital closure studies. This finding causes concern because many studies find evidence of racial inequalities with respect to access to health care. The elderly is another vulnerable population, and we find that urban hospitals in our study are significantly more likely to remain open as the number of elderly increases, a positive finding. However, we also find that hospitals in our study are significantly more likely to close with a high proportion of Medicare patients. This finding suggests that US government reimbursement for hospital care for elderly care may not be adequate. Finally, when examining hospital organization characteristics, we find that urban hospitals with a low occupancy rate and less severity of illness are more likely to close, as expected.
* * *
Based on our financial ratio hypotheses, we find that hospitals with high levels of debt are more likely to close--an expected finding. With respect to factors from the health services use model, we find that inner-city hospitals with a high proportion of minorities are more likely to close--a troubling finding. We also find that hospitals with high percentages of elderly in the community are more likely to remain open. However, once the hospital has an increasing proportion of Medicare patients, our findings reveal that it may be more likely to close. Some variables that capture hospital characteristics are significant predictors of hospital closure: low CMI and low occupancy rates, which again, as with high debt, is not surprising.
The most troubling finding is that as the number of minorities increases, hospitals may be more likely to close. Indeed, “racism is the most pressing cultural issue affecting access to health care.” Many studies have found inequities in health care access and quality care for non-white and low-income populations. Minority populations in inner cities are more likely to have lower income, higher unemployment, and less health insurance coverage. Closed inner-city hospitals may place a heavy burden on the uninsured, who often rely on hospital emergency rooms as their primary access to care, which may be further exacerbated by the current recession and high levels of unemployment.
A positive finding is that hospitals are less likely to close in areas with a high percentage of elderly, which is important as the US population ages. However, we also find that hospitals are more likely to close as the percentage of Medicare patients increases. These findings suggest that even though the elderly have access to care, Medicare may drain a hospital's resources, which may cause closure. This finding may indicate a serious concern for this very [p36] vulnerable group, particularly as US health care reform moves forward. Federal government reimbursement for hospitals may likely be reduced if we move to a national health plan to cover the underinsured and uninsured.
One obvious limitation to the study is that our sample covers a relatively short period of time and a limited number of urban areas. The composition of our open and closed hospitals may not be effectively capturing factors that affect hospital closure. Furthermore, our variables may contain measurement errors or additional factors not explored here which may affect hospital closure. From these limitations come suggestions to extend the research to more cities, and to examine other factors that may have caused hospital closure during other time periods.
However, our period of study was in a much more prosperous period, relative to today. We provide evidence that hospitals may not close just for financial (high debt) or operational (low occupancy rate) reasons. We find additional substantiation to the claim that some inner-city hospitals close in minority areas or with a large percentage of Medicare patients, which is important from a public policy perspective. Potential access to care for certain needy segments of the population may be at risk if inner-city hospitals that serve those populations close.
Kathryn J. Jervis, PhD, is an associate professor at the University of Rhode Island, Kingston.
Gerson M. Goldberg, PhD, is a Senior Lecturer in Finance at Northeastern University College of Professional Studies.
Alan C. Cutting is a professor of Computer Information Systems in the Gabelli School of Business at Roger Williams University in Bristol, Rhode Island, where he currently teaches courses in Web development, database design and implementation, business statistics and marketing on the Web.